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检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1897 条记录，以下是401-410 订阅

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Towards A machine learning Framework for Suicide Ideation Detection in Twitter 3

Towards A Machine Learning Framework for Suicide Ideation De...

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3rd international conference on Artificial Intelligence and Data Sciences, AiDAS 2022

作者： Lim, Yan Qian Lee, Ming Jie Loo, Yim Ling Universiti Tunku Abdul Rahman Department of Internet Engineering and Computer Science Selangor Malaysia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

A worldwide rise of number of individuals had been observed to commit suicide at young age since 2019. With emergence of digital technologies, more suicides attempts were seen to have been pre-communicated through social media posts before the attempts. As such, much initiatives had been conducted to detect communication of distress on social media which imply risks of suicide attempts or any related forms of self-harm. Such initiatives aim to predict the possibility of suicide attempts for prevention measures. This work proposes a framework for machine learning of suicide ideation detection in social media which will contribute to the prediction of possibility of suicide attempt in a social media post. The framework includes data acquisition, data annotation, data pre-processing, feature extraction, classification and performance evaluation of the machine learning model. Acquisition of social media post samples from Twitter is proposed for training and testing datasets through representational state transfer application programming interface. Manual annotation is conducted on the training datasets with different formulated suicide risks. Data pre-processing is done through natural language toolkit and performance evaluation through valence aware dictionary for sentiment reasoning. This work will be further extended with a web-based application for implementation and evaluation of the trained machine learning model. © 2022 IEEE.

关键词： Forecasting

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Federated learning with Blockchain: A Study of the Latest Decentralized Couple 3

Federated Learning with Blockchain: A Study of the Latest De...

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3rd IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022

作者： Faridi, Arman Rasool Hafeez, Aiman Masood, Faraz Aligarh Muslim University Department of Computer Science Aligarh India

ISBN: (纸本)9781665462006

Federated learning is a method for machine learning that avoids the need to move data by training an algorithm in parallel on a large number of edge devices or servers that hold copies of the training data in their own memory. Conventional decentralized approaches often assume that local data samples are equally distributed, whereas typical centralized machine learning techniques involve uploading all local datasets to a single server. Federated learning has flaws like privacy and insufficient data. Blockchain's rise offers a safe and effective method for Federated learning implementation. In this paper, the collaboration of Federated learning and blockchain is discussed. Then the possible applications that can be developed using federated learning and blockchain are discussed. Furthermore, the challenges and opportunities for collaboration between these technologies are explained. © 2022 IEEE.

关键词： Blockchain

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A Survey on Precision agriculture using machine learning 3

A Survey on Precision agriculture using Machine Learning

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3rd international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2022

作者： Prabhu, D. Dilip, Golda SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Vadapalani Campus Chennai India

ISBN: (纸本)9781665462754

In modern farming fidelity permits the precise application of information sources, such as toxicant, seed, manure, and effluent, at the precise moment of harvest in order to increase productivity and crop yields. Ranchers may readily determine the crops' range by tracking them using sensors that are collected from the fields, protecting the resources being used and reducing the impact of weeds on the environment. Most Indian ranchers use standard cultivating techniques to determine the crop yield that should be developed in order. In any event, the ranchers don't sacrifice crop productivity because it depends on the characteristics of the soil due to abiotic variables. This research suggestsa yield recommendation apparatus that encourages ranchers to select the appropriate crop to plant in their lands in this manner. selecting information about systems by machine. © 2022 IEEE.

关键词： Crops

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3rd international Symposium on the Education in Mechanism and machine Science, ISEMMS 2022

3rd International Symposium on the Education in Mechanism an...

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3rd international Symposium on the Education in Mechanism and machine Science, ISEMMS 2022

ISBN: (纸本)9783031257292

The proceedings contain 24 papers. The special focus in this conference is on Education in Mechanism and machine Science. The topics include: Evaluation of Audiovisual Guides for Laboratory Classes in Hydraulic machinery Courses of Distance learning Engineering Programs;learning How to Design and Manufacture by Applying Hot Wire Cutting to the Fabrication of a Car Spoiler;plans for a Course on the History of Mechanisms and machine Science;a European Researchers’ Night Project on Mechanical Vibrations for High School Students;Guizzo Xp: A Robotic Toolkit for STEM Education and Raising Awareness of Aquatic Environment Protection;Robotic Systems as a Part of AI Fundamentals Course at ITS Academy Foundation for New Life Technologies n.a. Alessandro Volta in Trieste, Italy;the Potential of Education and Training in Additive Manufacturing;matlab App for Teaching Planar Mechanism Kinematics;General-Purpose Software Tools in Teaching MMS;implementation of Projects Oriented learning in Mechanical Engineering Universities and Vocational Colleges;a Distance Teaching Experience in Gear Design with Autodesk Inventor;application of Reverse Engineering to Implement 3D Designs of Ancient Mechanisms;Has the Teaching Innovation Carried Out During the Pandemic Been Consolidated? DEM-UPC Subjects;Implementation of Audiovisual Material in Lab Sessions During COVID Time: Effects and Results;new Formative Evaluation Methodology on Rotating machinery Diagnostics;Developing Students’ Cognitive Skills in MMS Study Course;Kinematical Analysis and Dimensional Synthesis of RRPR-Type Four-Bar Mechanism in MMS Study Course;flipped Classroom and Technology Enhanced learning in Mechanical Engineering;flipped learning Applied to machine Design;dimensional Synthesis Approach of A Compliant Clutch Mechanism for a Formula Student Car (I).

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Research on 3D Animation Simulation Based on machine learning 3

Research on 3D Animation Simulation Based on Machine Learnin...

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3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum, AIBDF 2023

作者： Huang, Xinran Li, Panpan Tan, Yupeng Zhang, Yining Deng, Mengyuan Chengdu Neusoft University No. 1 Neusoft Avenue Qingchengshan Town Dujiangyan Irrigation Project City Sichuan Province China Fujian University of Technology No. 69 Xuefu South Road Shangjie Town Minhou County Fujian Province Fuzhou City China

ISBN: (纸本)9798400716362

The provided document is a research paper on 3D animation simulation based on machine learning, focusing on the application of machine learning in three-dimensional human animation technology. The paper discusses the importance of virtual reality technology based on computer three-dimensional animation in various fields such as film production, game development, sports simulation, and simulated training. The authors emphasize the significance of three-dimensional human animation technology in portraying subtle changes in human movement and simulating human emotions contained in movement. The paper also explores the application of machine learning methods in processing human body movement data and synthesizing new realistic movement sequences. Various machine learning theories and methods, including regression, function approximation, dimension reduction, classification, clustering, and decision-making, are discussed in relation to their application in three-dimensional human animation technology. The document also reviews the research status of human body movement synthesis technology at home and abroad, highlighting the contributions of various researchers in the field. The authors conclude that machine learning methods have unique advantages in processing human body movement data and can significantly improve the utilization rate of movement capture samples, thereby reducing the cost and time cycle of three-dimensional human animation production. © 2023 Copyright held by the owner/author(s).

关键词： machine learning

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Research on meteorological temperature prediction based on machine learning 3

Research on meteorological temperature prediction based on m...

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3rd international conference on Signal Processing and machine learning, CONF-SPML 2023

作者： Chen, Leyan Department of Computer Science Wenzhou-Kean University Zhejiang Wenzhou325060 China

Predicting temperature has been a great challenge in meteorology. Accurate temperature prediction is more conducive to human production and life. This study investigated the ability of artificial neural network (ANN) and random forest (RF) methods to predict short-term monthly temperatures. The study data has been processed from the global surface temperature change estimated by NASA Goddard Institute for Space Studies. The average temperature from three months ago, the average temperature two months ago, and the average temperature one month ago were used as inputs to the application model. Both the models gave comparable results, but the superiority of the artificial neural network model over the random forest model in the present study. © Published under licence by IOP Publishing Ltd.

关键词： Neural networks

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application of machine learning Techniques in Slope Failure Analysis 3

Application of Machine Learning Techniques in Slope Failure ...

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3rd IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022

作者： Biswal, Shatrujit Sahoo, Simanchal Sethi, Sudeep Ranjan Panda, Sameer Chelva, M.S. Das, Sameer Kumar Sahoo, Arun Kumar Pramanik, Jitendra Centurion University of Technology and Management Odisha India Karnatak Arts Science and Commerce College Karnataka Bidar India Bhubaneswar Biju Patnaik University of Technology Department of Computer Science and Engineering Odisha Rourkela India National Institute of Technology Rourkela Centurion University of Technology and Management Department of Mining Odisha India National Institute of Technology Rourkela Trident Academy of Technology Department of Mining Odisha Bhubaneswar India

ISBN: (纸本)9781665462006

With furtherance in the mining industry, accidents due to slope failure are getting frequent in mining sites. Slope instability being a complex process, it seriously threatens the miner's life and properties. The damage inflicted by slope failures in the recent past has pulled the attention of authorities toward implementing disaster risk reduction measures. This research work plays a dominant role in palliating the slope failure risk. The presented work demonstrates the potentiality of machine learning models in forecasting the stability of the slopes. We implemented the limit equilibrium method (LEM) in predicting the factor of safety (FOS) of the slip surfaces for the designed slope. With the application of machine learning (ML) models such as K nearest neighbours and Gaussian Naive Bayes, we further classified the slopes based on their degree of stability. The performance of ML models is examined and compared through quality metric parameters like accuracy and confusion matrix. © 2022 IEEE.

关键词： Safety factor

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Diabetic retinopathy detection using a pretrained machine learning model 3

Diabetic retinopathy detection using a pretrained machine le...

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3rd IEEE international conference on Electronics, Control, Optimization and computer Science, ICECOCS 2022

作者： Sbai, Asma Touil, Abdelali Oukhouya, Lamya Cady Ayyad University Laboratory of Bioscience and Health Faculty of Medecine and Pharmacy of Marrakech Marrakech Morocco Faculty of Sciences Ibn Zohr University Laboratory of Engineering Sciences Agadir Morocco Ibn Zohr University Laboratory LIMA ENSA Agadir Agadir Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

One of the possible side effects of diabetes is Diabetic Retinopathy. Early diagnosis of diabetic retinopathy is an important step toward healing and can prevent many patients from potential blindness. To identify diabetic retinopathy, practitioners may need an artificial intelligence tool to provide a second opinion to confirm or refute a diagnosis. In this article we use a pretrained machine learning model to find a solution to the issue of low-quality inputs by implementing, in the pre-processing step, the technique of Contrast Limited Adaptive Histogram Equalization to extract more features especially the blood vessels. © 2022 IEEE.

关键词： computer aided diagnosis

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Skin Cancer Detection Using machine learning: A Survey 3

Skin Cancer Detection Using Machine Learning: A Survey

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3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Desai, Ruchi Panchal, Juiee Mitra, Anjali Mamlekar, Shukur Chari, Harsha Aswale, Shailendra SRIEIT Goa University Computer Engineering Goa India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Skin Cancer is one of the hazardous types of cancer. It is basically an unusual growing of skin cells which mostly develops on skin contact with the sun. Nowadays it also develops on areas of the skin which is not in contact to sunlight. It is essential to detect cancer at prior or else it tends to gradually spread over the other parts of the body. Here we present numerous machine learning techniques that are used to identify various types of cancer and classify whether it is Malignant or Benign. There are four main steps included in the process namely Preprocessing, Segmentation, Feature Extraction and Classification. The Paper concentrates on the comparison of different types of methods which can be used for the above steps. © 2022 IEEE.

关键词： machine learning

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Securing Internet of Things Using machine learning Techniques: A Systematic Review 3rd

Securing Internet of Things Using Machine Learning Technique...

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3rd international conference on Communication, Networks and Computing, CNC 2022

作者： Kumari, Barkha Singh, Vinay Kumar, Mohit Usha Martin University Jharkhand Ranchi835103 India MIT-ADT University Pune412201 India

ISBN: (纸本)9783031431395

Our current period is the era of the Internet of Things (IoT). The latest evolution in information technology, software and paraphernalia have hastened the stationing of huge number associated smart and familiar appliances in evaluative system like industries, Agriculture, Healthcare, Transportation, Home automation and environment control. The data transmission over the network without necessitating of any human to human (H2H) or human to machine (H2M) role, increases the trustworthiness and customers satisfaction, but it also unlatched a gateway for attackers or intruders for executing various types of attacks for unauthorized access information manipulation or information disclosure which increases the security risk. machine learning technology is one of the optimum solutions to mitigate various security threats. In This paper a literature survey on a different security threat in a IoT technology and solution of security issues using machine learning approach and a brief explanation of different attacks in IoT applications has been presented. This work covers issues related to securing data generated in different application area of IoT system such as IIoT (Internet of Things for industries) and IoSHT (Internet of Things for smart healthcare system). The future scope of machine learning techniques to ensure safety and challenges are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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